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5G-Based Real-Time 2D Human Pose Recognition Prototype

Figure 1: 5G-based 2D human pose recognition prototype supported with real-time, low-latency. \scriptsize{1}⃝ Human vital-sign sensing and fall detection: RF echoes from the human body are used to monitor respiration, pose stability, and accidental falls. \scriptsize{2}⃝ Non-contact smart home control: Recognized poses and gestures drive device control and scene automation across multiple rooms. \scriptsize{3}⃝ Immersive entertainment interaction: Full-body tracking enables controller-free gaming and interactive multimedia experiences.

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Paper title: No Vision, No Wearables: 5G-based 2D Human Pose Recognition with Integrated Sensing and Communications Abstract: With the increasing maturity of contactless human pose recognition (HPR) technology, indoor interactive applications have raised higher demands for natural, controller-free interaction methods. However, current mainstream HPR solutions relying on vision or radio-frequency (RF) (including WiFi, radar) still face various challenges in practical deployment, such as privacy concerns, susceptibility to occlusion, dedicated equipment and functions, and limited sensing resolution and range. 5G-based integrated sensing and communication (ISAC) technology, by merging communication and sensing functions, offers a new approach to address these challenges in contactless HPR. We propose a practical 5G-based ISAC system capable of inferring 2D HPR from uplink sounding reference signals (SRS). Specifically, rich features are extracted from multiple domains and employ an encoder to achieve unified alignment and representation in a latent space. Subsequently, low-dimensional features are fused to output the human pose state. Experimental results demonstrate that in typical indoor environments, our proposed 5G-based ISAC HPR system significantly outperforms current mainstream baseline solutions in HPR performance, providing a solid technical foundation for universal human-computer interaction. Passages referencing this figure: Figure 1: 5G-based 2D human pose recognition prototype supported with real-time, low-latency. Using the controller-free 2D prototype shown in Fig. 1 as a reference, we detail three key scenarios, which include immersive entertainment, fitness guidance, and seamless smart home control.

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A reference image is attached above. It is my rough sketch of what I
want my final figure to look like — sometimes hand-drawn, sometimes
an AI quick-draft. The quality is rough; details may be wrong; some
elements may be missing — but it shows the STRUCTURE / SPATIAL LAYOUT
I'm going for.

I've also shared the paper title + abstract + method section + figure
caption + paragraphs that reference this figure.

TASK: Refine my rough sketch into a polished publication-quality figure.

  - Preserve the SPATIAL STRUCTURE of the sketch: where the boxes are,
    how they connect, the overall reading order, the rough proportions.
  - You may correct details: better text labels (use the paper context
    to get the right component names), cleaner shapes, real icons
    instead of stick-figure placeholders.
  - Do NOT regenerate from scratch with a different layout. The
    finished figure must be visibly the same composition as the sketch.

If your output bears no spatial resemblance to the reference sketch,
you've failed the task. Refine the sketch — don't replace it. Just
give me the polished figure.

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